In today’s world of big data and the internet of things, it is common for a business to find itself sitting atop a mountain of data. Possessing it is one thing, but leveraging it for data driven decision making is a much different ball game. Gut-feelings and institutionalized heuristics have traditionally been used to guide development of…

Forget #dataviz - As immersive #VR emerges we will experience #datarealization which is the experience of touching, smelling, sensing and physically manipulating data in an immersive data art exhibit.

Imagine putting on your #VR headset and you are in a chart. Not a bar or pie chart, but something totally new - an experience chart. You walk to the right and you see mountainous three dimensional structures. As you walk up to one you touch it and you hear a voice say “sales in December… Continue

More and more organizations today are moving to unified communications (UC) platforms for better communications within their organization, with their customers and with their partners. These platforms combine voice, email, chat and web into a seamless Omni-channel experience for its users. They today boost of a number of features, but most of them provide either static or rule based experiences. Given that these platforms generate tons of data, can this data be used to improve user…

We propose here a simple, robust and scalable technique to perform supervised clustering on numerical data. It can also be used for density estimation, and even to define a concept of variance that is scale-invariant. This is part of our general statistical framework for data science. Previous articles included in this series are:…

Summary: Management values the self-starting, data-driven, curious, and urgent characteristics that define the Citizen Data Scientist. But the path to encouraging these individuals also requires setting limits and risk procedures of a wholly new type. Procedures that will protect the organization so that bad analytic conclusions don’t become bad financial outcomes for the company.

A few comments for those who are about to invest on Machine Learning intensive project

During a conversation I had with Peter Norvig, we discussed about the kind of projects that we do at Machinalis and how strange does it feels to say that "we are a Machine Learning company": In many projects, the amount of effort spent on R&D on Machine Learning is usually a small fraction of the total effort, or it’s not even there because we plan it for a…

With the wide array of amazing data visualization tools out there - SAP Lumira, Qlik, Domo, Tableau - you would think that the world has moved towards a graphical understanding of reality.

Yet my experience has been that when people are faced with the task of using a fancy new graph or visualization in their work, their first reaction is….to freak out. Now bear with me now. I am not implying that most people can’t handle a nice bar chart or a three…

Social listening has a nasty habit of being completely soft—all about the words without the context of volume and velocity of conversation—or completely quantitative with little information about what’s actually being said. Unfortunately, this leads to conclusions that don’t help you make better strategic decisions. Whichever way your listening leans, you can’t get a clear picture of a situation or your brand online without both the qualitative and the quantitative.

Complex stuff! However, we can start from the basics , gain confidence in understanding our dataset and utilise whatever has already been done by other stalwarts!

We have a 11 years monthly data on milk procurement by more than 100 milk co-ops spread across India. This contains their geographic location, quality of milk procured, price received , products made etc etc. This is a seasonal industry in India affected by weather, prices and in general crafty management acumen…

Analytics is still in a phase in many organizations where selling it internally to the stakeholders is the biggest challenge.Creating analytics is a cost- resource intensive investment for enterprises and evangelizing the trust in data driven thinking and optimizing the opportunity cost due to delay in adoption is the most crucial problem to solve.

All the frameworks which talk about the Analytics mix, various technology & tools stack and maturity roadmaps, are confined to…

What’s the real value of data science? Hailed as the sexiest job of the 21st century just a few years ago, there are rumors that it’s not quite proving its worth. Gianmario Spacagna, a data scientist for Barclays bank in London, told Computing magazine at Spark Summit Europe in October 2015 that, in…

Telecom industry is one which not only sees a large customer base, but a customer base who’s needs and desires are constantly evolving and/or shifting. On top of this, telecom firms face cut throat competition, making it a highly dynamic and challenging industry. In such a scenario, each decision that a telecom firm takes becomes all the more crucial. It is hence imperative for the firm to take decisions based on extensive data analytics so as to ensure efficient and effective use of…